Search results matching tags 'Cloud Computing', 'Trends', 'Hadoop', and 'Performance'http://sqlblog.com/search/SearchResults.aspx?o=DateDescending&tag=Cloud+Computing,Trends,Hadoop,Performance&orTags=0Search results matching tags 'Cloud Computing', 'Trends', 'Hadoop', and 'Performance'en-USCommunityServer 2.1 SP2 (Build: 61129.1)Getting Ahead of the Curve – Big Datahttp://sqlblog.com/blogs/kevin_kline/archive/2011/07/14/getting-ahead-of-the-curve-big-data.aspxThu, 14 Jul 2011 14:41:00 GMT21093a07-8b3d-42db-8cbf-3350fcbf5496:36935KKlineI have to confess that I'm incredibly excited about BigData. I haven't been this excited about new innovations in IT since relational databases first appeared on the scene early in my career. But what is BigData?
Back in those days, I can still feel the echos of adrenaline when I was hired to work on a NASA project that would involve over 100Mb of data. <span style="text-decoration:underline;"><strong>ONE HUNDRED MEGABYTES!</strong></span> Good grief, that was fantastically huge to us on the team. (That database was over 130Mb when I finally moved on to another project). And remember - PC software was installed using 640Kb floppy disks at the time. In fact, my Oracle v5 instance required shuffling through about a dozen floppy disks to get the thing installed on a 286 IBM PC.
BigData today takes on an entirely meaning as database sizes scale into the petabytes. But the emphasis is still the same today as it was back in the 1980's - <em>turning data into actionable information</em>. However, with BigData, we can achieve amazing new insight from this data and mine for tidbits that would never have seen the light of day with smaller data sets.
The two major themes to remember about big data are 1) the more data you have on a given domain, the more power you have, 2) the better the <span style="text-decoration:underline;">analysis</span> you can perform on the data, the more power you have. In fact, theme 2 might be the most important thing to consider because lots of data is meaningless unless you can extract knowledge from it. And that's where better analytical techniques come into play.
Here are some articles about Big Data that you might enjoy:
<ul>
<li><a href="http://blogs.infor.com/inside/2011/05/introducing-big-data.html" title="Bruce Richardson, CIO of INFOR" target="_blank">Bruce Richardson Introduces Big Data</a></li>
<li><a href="http://www.mckinsey.com/mgi/publications/big_data/index.asp" title="McKinsey Global Institute" target="_blank">McKinsey Global Institute Report on Big Data</a></li>
<li><a href="http://sqlblog.com/controlpanel/blogs/Chris%20Boorman:%20Big%20Data%20is%20Coming,%20Are%20You%20Prepared" title="Chris Boorman of Informatica" target="_blank">Chris Boorman: Big Data is Coming, Are You Prepared?</a></li>
<li><a href="http://www.ramonchen.com/?p=3170" title="Ramon Chen's Great Blog on Cloud Computing" target="_blank">Ramon Chen: LinkedIn's IPO - A Perfect Storm of Big Data, Open Source and Cloud Computing</a></li>
<li><a href="http://allthingsd.com/20110526/seven-questions-about-big-data-and-analytics-for-ibms-steven-mills/?refcat=enterprise" title="Arik Heeseldahl: From the Wall Street Journal" target="_blank">AllThingsD: Seven Questions About Big Data</a></li>
<li><a href="http://www.smartercomputingblog.com/2011/05/26/a-match-made-in-heaven-data-quality-and-big-data-a-lesson-from-the-past/" title="Andrew Manby on the SmarterComputing Blog" target="_blank">SmarterComputingBlog: A Match Made in Heaven - Data Quality and Bid Data</a></li>
</ul>
Let me know what you think. Best regards,
-Kev
<div><span style="font-family:'Times New Roman';"> Follow me on <a href="http://twitter.com/kekline" title="C'mon. You know you want to!" target="_blank">Twitter at kekline</a></span></div>